Question

The following table provides information on life expectancies for a sample of 22 countries. It also lists the number of people per television set in each country.

1- Since the association is so strongly negative, one might conclude that simply sending television sets to the countries with lower life expectancies would cause their inhabitants to live longer. Comment on this argument.

2- If two variables have a correlation close to +1 or –1, indicating a strong linear association between them, does it follow that there must be a cause-and-effect relationship between them?

Country	Life Expectancy	People Per TV
Angola	44	200
Australia	76.5	2
Cambodia	49.5	177
Canada	76.5	1.7
China	70	8
Egypt	60.5	15
France	78	2.6
Haiti	53.5	234
Iraq	67	18
Japan	79	1.8
Madagascar	52.5	92
Mexico	72	6.6
Morocco	64.5	21
Pakistan	56.5	73
Russia	69	3.2
South Africa	64	11
Sri Lanka	71.5	28
Uganda	51	191
United Kingdom	76	3
United States	75.5	1.3
Vietnam	65	29
Yemen	50	38

the correlation coefficient is -0.8039

Answer 1

Correlation coefficient usually not indicate cause-and-effect relationship. If the 2 variables are such that they get impacted by other factors than observing correlation between them is os very little use. For instance, average speed of cars is a country and Per capita income doesn't have any direct relation, so, correlation can't be taken as a measure here as many factors impact the per capita income and it's hard to pin to one specific feature.

In the present case, it could be that countries with lesser age expectancy doesn't have other medium of entertainment and hence, opt of television in home. In such case it having positive or negative correlation doesn't indicate any cause-effect relationship.